Hi Sourav, Yes, GLM-predict.dml gives out only the probabilities. You can put a threshold on the resulting probabilities to get the actual class labels -- for example, prob > 0.5 is positive and <=0.5 as negative.
The exact value of threshold typically depends on the data and the application. Different thresholds yield different classifiers with different performance (precision, recall, etc.). You can find the best threshold for the given data set by finding a value that gives the desired classifier performance (for example, a threshold that gives roughly equal precision and recall). Such an optimization is obviously done during the training phase using a held out test set. If you wish, you can also modify the DML script to perform this entire process. Shirish On Tue, Dec 8, 2015 at 12:23 PM, Sourav Mazumder < [email protected]> wrote: > Hi, > > I have used GLM.dml to create a model using some sample data. It returns to > me the matrix of Beta, B. > > Now I want to use this matrix of Beta on a new set of data points and > generate predicted value of the dependent variable/observation. > > When I checked GLM-predict, I could see that one can pass feature vector > for the new data set and also the matrix of beta. > > But I could not see any way to get the predicted value of the dependent > variable/observation. The output parameter only supports matrix of > predicted means/probabilities. > > Is there a way one can get the predicted value of the dependent > variable/observation from GLM-predict ? > > Regards, > Sourav >
